Impact of four-dimensional variational data assimilation of atmospheric motion vectors on tropical cyclone track forecasts

The fifth-generation Pennsylvania State University-National Center for Atmospheric Research nonhydrostatic Mesoscale Model is employed to evaluate the impact of the Geostationary Meteorological Satellite-5 water vapor and infrared atmospheric motion vectors (AMVs), incorporated with the four-dimensional variational (4DVAR) data assimilation technique, on tropical cyclone (TC) track predictions. Twenty-two cases from eight different TCs over the western North Pacific in 2002 have been examined. The 4DVAR assimilation of these satellite-derived wind observations leads to appreciable improvements in the track forecasts, with average reductions in track error of ∼5% at 12 h, 12% at 24 h, 10% at 36 h, and 7% at 48 h. Preliminary result suggest that the improvement depends on the quantity of the AMV data available for assimilation. © 2006 American Meteorological Society.